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Lead Data Scientist
Skills
Google BigqueryMachine ToolsSparkPySparkSQLData WarehousingPython
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 15+ years of professional experience as an applied Data Scientist
- 3+ years in telecom broadband wireless or subscription data
- Strong SQL Spark and PySpark experience
- Advanced Python with pandas NumPy scikit-learn XGBoost and LightGBM
- Deep understanding of core machine learning fundamentals
- Experience with class imbalance feature selection and calibration
- Ability to evaluate models using lift precision recall and ROI
- Practical geospatial SQL experience with GIS spatial indexing
- Hands-on feature engineering on cloud data warehouses
- Experience with A/B testing RCTs and model explainability
- Ability to manage production monitoring and data drift
Nice to have
- Business-focused
- Analytical
- Detail-oriented
- Collaborative
- Hands-on
Day to day
- Lead hands-on development of propensity and segmentation models for telecom data using SQL and Python.
- Build clean feature sets from large cloud warehouse tables spanning billing network performance competitive footprint and geographic data.
- Develop clustering calibration and business-focused model evaluation outputs that support marketing optimization and actionable target lists.
Hiring process
- Share requested details and updated resume
- Interview availability
- Project availability